As a frequently used information search system, a search engine helps users to search information required by the users. For example, when a user inputs a search term “anti-haze mask” at a search page, the search engine may search for a plurality of websites or applications relating to the search term “anti-haze mask”.
In order to facilitate the users to perform a search conveniently and efficiently, a plurality of search recommendations relating to the search term may be automatically generated and provided to the users to choose after the users input the search term. At present, generation of a search recommendation is mainly based on a user search history. For example, if the user has searched terms such as “anti-haze mask price,” “anti-haze mask model,” etc., after the user inputs a term “anti-haze mask,” search recommendations such as “anti-haze mask price,” “anti-haze mask model,” etc. may be provided at a search page through means of a drop-down menu, etc.
However, the conventional method for providing search recommendations based on search history obviously has a narrow selection range of search recommendations. The users often need to search many times, thereby consuming a lot of time and network traffic.